Latest / The Learning Corner by Precursor / Episode #88: Supporting Young Founders Well, YC's Fall Requests For Startups, Why Labs Say Frontier Not Foundation

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Episode #88: Supporting Young Founders Well, YC's Fall Requests For Startups, Why Labs Say Frontier Not Foundation · The Learning Corner by Precursor

• 0:00
  The irony is we're going back to the future, back to the days where the government was a
• 0:04
  really big funder and early customer of innovative entrepreneurial technology products.
• 0:10
  It wasn't always the big primes.
• 0:12
  In some ways, it feels like we're going back to the future.
• 0:15
  It's the week of July 27.
• 0:18
  Welcome to the Learning Corner, a Precursor Ventures podcast.
• 0:23
  Welcome to the Learning Corner by Precursor.
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  I'm Mia Farnam, and I'm joined by our GP and managing partner, Charles Hudson, where we will
• 0:29
  be talking through articles and Goodreads that caught our team's attention over the past week.
• 0:35
  We've also got an awesome guest joining us this week.
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  Alina, one of our incredible interns who's been here for almost six months.
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  We're so excited for you to join us here.
• 0:44
  Thanks for having me.
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  I'm so excited for the discussion.
• 0:47
  Awesome.
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  Well, lots to talk about this week.
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  Our first good read this week comes from Ashley Smith at Vermillion Cliffs Ventures, riffing
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  off a TechCrunch conversation she had on backing founders under 20 years old.
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  She argues today's young founders face a different kind of pressure than the last cycle
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  since AI era expectations want a working growth engine within months, not just years.
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  And the patience that used to come with early capital has mostly disappeared.
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  She's also blunt about the rise of predatory incubators that hand out small checks for
• 1:21
  outsized equity stinks, warning that a young founder can end up with a cap table too damaged
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  to raise a real next round before they've proven anything.
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  Ashley points to Cursor's trajectory as a case in point, a genuine outlier that too many funds
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  and founders are now treating as the baseline expectation.
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  And our closing argument is that investors owe young founders far more honesty about how
• 1:45
  normal failure is at the earliest stages, even when that honesty is very uncomfortable to
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  deliver.
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  We've talked about young founders on the podcast many times, and I think we've talked
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  about it from the standpoint of separating being a founder, and being willing to take risk
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  with just being young.
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  I think Ashley touches on a lot of different aspects that we haven't blown out in much
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  detail, like the predatory incubator aspect, making sure you're a little bit more diligence
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  on the difference between success and failure early on.
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  I think one great quote from Ashley when she compares cycles of this prior to today was,
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  quote, capital is available, but the patience that used to come with it at the earliest
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  stages isn't.
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  So Charles, wanted to pause here first to see if you had any specific reactions to the
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  overall piece and and not the poet specifically.
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  I agree with Ashley.
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  Like, there isn't a lot of patience.
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  I worry a lot more with these younger founders about I but not about IQ, but about EQ and,
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  like, this managerial journey they're gonna go on just like every other first time founder we
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  work with.
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  I think right now, though, it's not just that there's not patience.
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  It's also that the expectations around how quickly good things can compound in this market
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  have never been higher.
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  And I also couple this with the fact that, you know, we've talked about this internally.
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  We go through cycles where at times dropping out is a high status thing to do because as
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  Ashley mentioned, she's of the generation where finishing college was the thing that you did.
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  So dropping out was like a high risk thing to do.
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  Now I feel like, particularly if you're at a top 10 school, it's so difficult to get into
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  those schools that there's a bunch of students who feel that dropping out has become a low
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  risk activity, which to me means it's low signal.
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  It's funny.
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  Yeah.
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  I mean, I graduated from college in 2000, and I had a ton of friends in '99 who dropped out of
• 3:34
  school to do Internet startups.
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  Most of those companies weren't successful, but many of those people discovered that
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  entrepreneurship was gonna be a big part of their future career.
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  And my expectation is that the results here will be pretty similar.
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  Many of these companies will be unsuccessful, but many people will realize that being a
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  startup founder or being an entrepreneur is something they want for the rest of their
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  career, and learning that early has value.
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  I think one of the things that I thought about the most after reading the article was I have
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  no issues with young founders flooding the space, being excited, and bringing all that
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  entrepreneurial energy into the ecosystem.
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  That's fantastic for us.
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  For our jobs, it's fantastic for the ecosystem.
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  I think it just calls into play the question of, is the infrastructure laid out to help
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  support young founders who maybe didn't have all the mentorship or, I don't know, truthful
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  conversations about what are some predatory things that could happen to you along the way
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  that you might build.
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  I mean, we it it is similar to first time founders too.
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  A lot of founders don't know that there are specific predatory terms that exist for some
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  incubators versus others.
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  There are some that have different signals than others do.
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  I don't know if necessarily every first time founder has an information, and I would say the
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  same is about young founders.
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  So I think it's more of, are the rails ready to help support this flood of new founders, new
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  energy into the system in the way that I would hope that they are?
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  I think one thing I think about a lot is I've been fortunate enough to hear a lot of
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  interviews with Dylan, the CEO of Figuen.
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  Then I just think about all the people, like notably John Lilly, who were super experienced,
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  not just as entrepreneurs and founders, but as people who understood how to navigate the
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  valley in fundraising ecosystem.
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  And my my sense is that having those people around the company was really, really helpful
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  in its development, and I just wonder who's advising, supporting, and helping this next
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  generation of really young founders figure all of these things out.
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  Because as much as things have changed with AI, a lot of things about company building, you
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  gotta find great people, you've gotta be a great leader, you've gotta figure out how to
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  scale yourself.
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  Those principles haven't changed.
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  And I think on that note of truthful conversations, Ashley also argues that
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  investors have this responsibility to be honest with young founders earlier sometimes than
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  might feel comfortable about the failure rates and what the hard parts of being a founder
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  actually look like.
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  I'm curious.
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  How do you be honest about that without getting in the way of that fearlessness that can make
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  young founders so special?
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  I think one of the challenges for a lot of young first time founders is, like, knowing
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  when the answer is to change ideas versus to stick with it.
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  And I think, as you mentioned, Alina, a lot of the young founders, I mean, have what feels
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  like boundless energy.
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  And so, like, the capacity to work isn't the issue.
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  But not every problem is an effort problem.
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  Some problems are, hey.
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  You're just pointed in the wrong direction.
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  What you're willing to do is actually take a step back and, like, look at whether the thing
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  that you're building makes sense, whether it's still a good idea, whether it's still worthy of
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  your time.
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  And I think this sort of unbridled, unbounded amount of time that young founders have
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  sometimes means they just keep going when maybe the answer is to actually press pause.
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  I think Ashley had a really good quote here.
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  And she said, for a young founder who hasn't watched peers go through the harder parts yet,
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  that silence creates a distorted map.
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  Not knowing what to be afraid of can be a strength, but so can the myth that if you build
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  something great, it will succeed.
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  Great products fail every day, and she said a different word, but bad products make it also.
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  I mean, it's so true.
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  And I think, again, we talk we're talking about this a lot.
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  There's a lot of parallels between first time founders and young founders of just you're only
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  privy to the things that you see in media and the headlines that come through.
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  And so if you truly believe, if I bring a good product to market and it works, then people
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  will come and it will be the one that people grasp.
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  That we've seen so many examples of that not working.
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  Bad products hit the market every day.
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  Like, that's just not something that's new.
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  You also just made me think about one other thing that's different is I think a lot of
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  young entrepreneurs I met back in the day had very little contact with startup formation or
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  fundraising.
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  And now with the proliferation of on campus scout programs and VCs, mining college
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  campuses, trying to find the next generation of entrepreneurs, I've met many more people who
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  they're kind of wise beyond their years in the sense that they, like, are familiar with how
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  cap tables work.
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  They know what a safe is.
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  They have some sense of who the good invest like, they're just more familiar with the
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  ecosystem and, like, that part of it, but that's a very different part of the process
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  than actually building a company.
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  Our next good read is y Combinator's fall twenty twenty six request for startups where y
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  c partners and outside voices lay out the problems that they want founders to build for.
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  This batch centered on AI moving into the physical world, expanding categories from
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  multiplayer AI tools to compute at sea, to even rebuilding trust online as deepfakes get
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  cheaper and more convincing.
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  The one that stood out the most to me was the request from the sitting US secretary of the
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  army, which seems to be the first time that a government official has contributed to the
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  list, calling for founders to build low cost interceptors, next gen sensors, and hardware
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  that plugs into the army's new open system architecture.
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  Across the list, YC seems to be betting that the next generation of durable companies gets
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  built at the intersection of AI and the physical world, not purely software.
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  I'm curious, Charles.
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  It seems like the army secretary putting out this request for defense solutions via YC and
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  going straight to start ups instead of traditional procurement is something different
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  and maybe big.
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  I'm curious what do you think this implies for the start up ecosystem?
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  It's funny.
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  I always find the YC request for start ups to be an interesting list for two reasons.
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  One, it usually reflects some flavor of sci fi.
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  And I was like, when I read about the always on AI tutor, was like, that's a Neil Stevenson
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  reference as they mentioned, but so is the compute at c.
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  I don't know if anybody's read Crypto Nalakon.
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  I was like, sea stutters, these are these are ideas that have been talked about in the past
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  in science fiction.
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  I read the list, I was like, these all seem like near term, high probability things that
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  can be solved with tech today.
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  And when I read this, I was like, these are problems that if you're already working on, you
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  should probably be excited that there's an audience for.
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  But if you take this as a list of things you should start, my hunch is you're probably too
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  late.
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  And if I think about many of the great companies that I've met through YC in the,
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  whatever, over a decade I've been going to Demo Day, many of them were pioneering new
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  categories, were taking advantage of things that had just become feasible but weren't yet
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  well understood to be big ideas.
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  The irony is we're going back to the future, back to the days where the government was a
• 10:25
  really big funder and early customer of innovative entrepreneurial technology products.
• 10:30
  It wasn't always the big primes.
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  There was a lot of overlap between the government and Silicon Valley, and it brought
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  us a lot of really important innovations.
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  And in some ways, it feels like we're going back to the future.
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  Alina, know we were talking about this before you even started recording.
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  But if we have a government official making a request for startups, will that change
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  potentially what the procurement cycle looks like for them?
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  And again, hand in hand with the conversation that we just had earlier, the age of YC
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  founders continues to drop every year.
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  So what does that look like when you have younger folks going through government
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  procurement cycles in a way that they haven't prior?
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  Again, I think part of this is wonderful marketing and making sure that they get really
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  great people to or notable people to come up and walk through what the requests look like.
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  But also, it makes you question like, oh, what would this look like if it actually came into
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  play?
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  I mean, we've seen young people start coming into the government.
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  We had doge happen, so that's not, like, the first time something like this has occurred.
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  But it does make me wonder, how do you actually put this in play?
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  And I think, Alina, you had a good comment earlier of, do you think this will be the
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  beginning of newer cameos from tour leaders of different industries making an entrance into
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  the request for startups YC batch to kind of ask and and call for new ideas that can help
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  them push the needle.
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  And then I wonder always if that's going to help them make the decision on, do you think
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  they'll buy or build whatever comes from?
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  Do you think they'll use it as inspiration, or do you think they really will partner with all
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  the folks who are building in this YC batch?
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  To my excitement, the YC list also signals that consumer is back.
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  I have not seen that come up in batches in many cycles.
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  Their argument is that every platform shift mints new consumer giants.
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  Get three years in, and I think ChatGPT is likely the only big app that's hit most
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  people's iPhones since things have hit the market even when it's getting cheaper to bill
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  in consumer year over year.
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  Precursor, like, remain bullish on consumer even when so much of venture capital was
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  running away from the industry.
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  What, Charles, do you think other investors are seeing now or maybe signals of that they hadn't
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  seen before?
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  It's pretty funny.
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  I was talking to one of our longest tenured LPs.
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  He's been with us since the very beginning.
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  And he said, I think it's really interesting that you have companies in all of these
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  categories that are doing well.
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  And I said, well, I don't tend to think in terms of categories.
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  I think in terms of founders and ideas.
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  I don't think we've ever had a year where consumers been less than 20% of what we do, and
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  we've had years where it's been half.
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  As great as AI harnesses and inference and compute are, there's nothing quite like finding
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  a consumer experience that really touches people's lives.
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  Like, I've made a few investments lately in consumer that will hopefully come out soon that
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  I think are tackling like really important problems in really novel ways.
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  I do think in some ways, consumers always had this problem of differentiation and moat.
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  Most things you could build in consumer are relatively lightweight, simple experiences.
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  The the real knack is, like, how do you find an audience that wants them?
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  And I think about things like Twitter, not a not a in the beginning, not a technically
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  complicated product just happened to really strike a nerve for people.
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  Instagram, Snapchat, a lot of these products really, like, tap a nerve, and so I'm glad to
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  see that YC is open for business for consumer startups again.
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  And I will say this, I tend to see certain categories like the AI powered parent assistant
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  apps.
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  I've probably met 10 of them all started by really great people that are all really smart,
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  but all kinda have the same idea.
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  Yeah.
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  And so I think we will probably see hyper concentration in some of the obvious categories
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  to consumer, and I hope that that ends up producing some really great experiences for end
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  users.
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  And going off that line, I think we've had conversations about that, Charles, of what are
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  subcategories where maybe we don't need tech as or maybe tech isn't the solution to maybe
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  helping folks find a better way.
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  I think we also talked about that a lot with, you know, parental controls on tech with kids.
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  Like, not like I I don't think that there's going to be something that wins there.
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  I just think that the consumer itself has to evolve to get comfortable with, you know, how
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  do they see AI or tech sitting in their day to day lives within family.
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  I just look at, like, Tin Can.
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  I look at all the people who've been, like, trying to get kids off of screens and trying to
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  get and I was like, if you think of the screen not just as an entertainment experience for a
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  young person, but also as a communication experience, it becomes very clear that, like,
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  if you're gonna take away the entertainment experience, you have to, like, replace it with
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  something that allows them to communicate and talk to each other.
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  And it turns out that a landline phone is awfully good at that, particularly if the
• 15:27
  people in question mostly are at home.
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  And I think, like, not everything has to be some LLM powered, agentic solution.
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  Sometimes it's just like looking at existing problems and thinking about more clever ways to
• 15:40
  solve them.
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  And I hope that this next wave of consumer comfies also includes some of that energy too.
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  I think especially since people have such a desire for IRL, and we see that with all these
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  connection economy type of apps that are coming out, it'll be interesting to see how there's
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  that competing desire for in person connection and then also the height of what consumers can
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  get from AI, you know, where those things overlap and where they diverge.
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  And I think the one question that I ask consumer founders who are building in those
• 16:10
  specific spaces are how do you keep the magic coming up every single time?
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  I think there are so many different apps and new things that come up that the first time you
• 16:18
  use it, it's the most magical fun experience.
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  You blast it off to 15 of your friends.
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  You're like, you have to use this with me.
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  And then by use four, five, six, the magic wears off, and your friends have certainly
• 16:30
  abandoned it.
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  But if you can instill something that continues that thereafter, that's what that's what
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  creates the long term durability.
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  And I think that's a really difficult thing to start.
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  So to your point, Charles, it's not that it's easy, but it's lightweight to build something
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  that has a simple, a solve to a personal consumer facing problem.
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  Very difficult difficult task to make that defensible over years, which is why companies
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  like X, Instagram, just they are truly giants in that industry because they keep people
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  coming back.
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  And, Charles, I'm curious if you were writing some sort of precursor request for startups,
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  what would be on that?
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  Is there anything that you wish more founders were working on that you're not seeing enough
• 17:14
  of right now?
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  It's so funny.
• 17:16
  I feel like all of my co investor friends are always like, what are you looking for?
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  And like, I honestly don't know.
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  I only know what's gonna peak my interest when I see it.
• 17:27
  It's a terrible answer, Alina, to tell people when they're like, are you looking for?
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  You're like, I don't know.
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  But that that's, like, the most honest answer.
• 17:35
  And every time I've tried to write down these are the things I think I wanna see, it usually
• 17:40
  ends up being like, oh, I've seen a bunch of bad versions of thing x is somebody else.
• 17:45
  I ended up funding a team that's doing something in the screen time limiting usage
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  space, and I've seen some hardware solutions.
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  I've seen some software solutions, and none of them felt quite right.
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  And I thought the team that we ended up backing is certainly doing something different.
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  I don't know if it will work, but they have, like, a different conceptualization of, like,
• 18:05
  what the problem is.
• 18:07
  And I'm I'm, like, like, genuinely curious to see how it works.
• 18:10
  And I kinda feel the same way about a lot of categories where I'm like, oh, I've seen eight
• 18:15
  or 10 versions of why this doesn't work.
• 18:17
  If someone could show me a version that does, I'm all ears.
• 18:22
  You made an investment in this company, Blue Core Energy, and a bunch of my friends are
• 18:26
  like, oh, you guys are doing energy now?
• 18:27
  I'm like, not really.
• 18:30
  I'd I'd made this investment at this company because I like this founder's specific idea.
• 18:36
  It's not that I now have a general thesis on energy.
• 18:40
  And I think so many people are people want you to have, like, some overarching global thesis
• 18:45
  of how the world works, and I'm just like I just, like, follow the people.
• 18:49
  I try to find the best people I can who are working the most interesting problems and,
• 18:52
  like, work with them on it.
• 18:53
  And then I learn and then I learn about these other adjacent problems.
• 18:56
  And so I don't know.
• 18:57
  Guess that's why I've never had one.
• 18:59
  Cool.
• 19:00
  Well, our last Goodread piece is by Chris Peck called Frontier, and it explores why AI Labs
• 19:08
  stopped calling their models foundation models and started calling them frontier models.
• 19:13
  He says that a foundation implies something durable that you can build on top of and
• 19:17
  collect rent from forever, while a frontier is something that you can only hold temporarily
• 19:21
  and have to re earn with every single new release at rising cost.
• 19:25
  The piece argues that labs are essentially betting that demand for AI capability is
• 19:30
  unbounded, so the frontier never closes and a good enough competitor never catches up to
• 19:35
  squeeze their margins.
• 19:36
  It draws this comparison to AOL, which was once inseparable from the Internet itself until
• 19:40
  competition caught up with it and a distribution advantage disappeared.
• 19:44
  The author points to agentic coding as the current battleground where falling prices and
• 19:49
  strong open weight models are already chipping away at the profit pool that labs are counting
• 19:54
  on.
• 19:55
  Charles, if the Frontier never closes the way that labs are betting that it will, then does
• 20:02
  that make them a better or a worse venture bet than a company that is selling something with
• 20:07
  durable moat sooner?
• 20:08
  I think we're in sort of an interesting moment in the cycle.
• 20:13
  I think for a while, everyone's like, oh, the Frontier Labs are gonna win everything.
• 20:17
  We're all gonna be paying Anthropic and and OpenAI and maybe Google Gemini forever.
• 20:24
  We're gonna be, like, constantly paying this tax and rents to them because they have this
• 20:28
  interesting bundle of, like, LLM capabilities and inference and training and, like, we're
• 20:33
  gonna be stuck on their infrastructure.
• 20:34
  It's gonna be the next AWS.
• 20:36
  Now I think we're in a moment where people are saying, oh, that's like the old like, that's
• 20:40
  like driving a Ferrari to the grocery store analogy.
• 20:43
  Why would I wanna use some high end model to convert a PowerPoint to a spreadsheet?
• 20:48
  Shouldn't I use an open source model?
• 20:50
  I think the answer is, like, people are gonna get smarter about this stuff now that cost is a
• 20:55
  part of the equation.
• 20:57
  And now that cost is a part of the equation, people are gonna say, well, do I need to use
• 21:01
  the fanciest, most sophisticated models?
• 21:03
  The right answer isn't actually an open source model.
• 21:06
  It's a cheaper version or an older version of one of the hosted models because they work fine
• 21:10
  unless you're an open source purist.
• 21:12
  And I I really do think that if I were at one of the big frontier model companies, my belief
• 21:18
  would have to be that there will always be new hard to solve problems in AI.
• 21:23
  Will there be an audience where only we have the resources to tackle this problem?
• 21:28
  It could be biology.
• 21:29
  It could be physics.
• 21:30
  It could be math.
• 21:32
  I would say coding, we're approaching the point where, like, maybe you don't need the most
• 21:36
  sophisticated model in every case.
• 21:39
  But there are lots of domains where that hasn't happened, and so if I were trying to make the
• 21:42
  bull case for the frontier models, would just say there will always be a new category
• 21:47
  vertical or area of exploration where a frontier model gives you the best answer.
• 21:52
  And if I were an open source zealot, I'd be like, over time, that window of things where
• 21:57
  you need the most fancy frontier model is going to shrink.
• 22:01
  And it's not gonna shrink to nothing.
• 22:03
  It's just gonna shrink to the point where people will use cheaper or open source models
• 22:08
  to do more things.
• 22:09
  And I'd argue that, like, history has shown me at least, if you think about AWS, you would
• 22:14
  have said, well, eventually, like, people will start hosting their own infrastructure again.
• 22:18
  A few companies have.
• 22:19
  But in many cases, you're like, oh, like, the world that AWS enabled became its own
• 22:24
  ecosystem, which became even more complex.
• 22:26
  And so at some point, you're like, well, it's not just like the hostings.
• 22:29
  The hosting and the routing and the bandwidth and the load balancing and, like, to replicate
• 22:33
  all of that stuff, the problem becomes bigger and bigger over time.
• 22:36
  I suspect that AI is gonna have the same trajectory where you're like, well, yeah, I
• 22:40
  could have I could run a local version of this on my computer or I could tap this cheaper
• 22:45
  model.
• 22:45
  But what about inference, training, memory, all the other pieces that go around it?
• 22:50
  And I'm not sure that we're quite ready to unbundle.
• 22:55
  If you think about what OpenAI and Anthropic offer really is a bundle, that old Jim
• 22:58
  Barksdale, there's only two ways to make money, bundling and unbundling.
• 23:02
  I think the unbundling phase feels premature.
• 23:05
  Yeah.
• 23:05
  I agree.
• 23:06
  I I do think that for frontier models to continue to keep their speak, I think two
• 23:12
  things need to be true.
• 23:13
  There needs to be continuous, like, unbounded demand, and they need to continuously deliver,
• 23:18
  like, a higher tier of capability.
• 23:20
  And the people who use our product need to care enough to what you're saying, Charles.
• 23:25
  Like, if the average person I'm only talking about d to c, but b to b is a completely
• 23:30
  different conversation.
• 23:32
  If I'm only talking about D2C, basically, do you need that higher tier capability to do the
• 23:37
  task that you set it out to do?
• 23:39
  And if the answer is no, then do you need to continue to pay, I don't know, dollars 20 to
• 23:43
  $200 a month for it, or could you seek capabilities elsewhere?
• 23:47
  And look.
• 23:48
  We we're probably in the, like, $5 Uber era of open.
• 23:52
  And I think it's interesting, like, in a lot of ways, everyone's like, oh, well, like, Uber is
• 23:57
  so expensive and, like but it's become an ingrained habit, and people use it.
• 24:01
  And I use it in all kinds of use cases where I would have never used it before.
• 24:05
  Maybe not as happily as I did when it was cheap.
• 24:08
  And I have a feeling that the the reason I think it's probably too early to talk about
• 24:12
  unbundling is outside of power users, most people are have barely started to scratch the
• 24:18
  surface of what this technology could do.
• 24:22
  And the only people who I think have are the ones who are pushing it to the limit.
• 24:27
  And those are the people who are experiencing both the pain and cost of being on the
• 24:31
  frontier.
• 24:32
  And I think it's natural for those people to say, well, now that I've used these a lot it's
• 24:36
  funny.
• 24:36
  I started running a bunch of my other evals on my own work, and I have downgraded a bunch of
• 24:41
  the models I used to use because I'm like, I can get almost similar performance at a
• 24:45
  fraction of the price using a different model.
• 24:47
  But that's, like, mostly out of my own curiosity and desire to keep our AI
• 24:52
  expenditures Yeah.
• 24:53
  At a level that I'm willing to pay for.
• 24:55
  But if I weren't using it as intensely, it wouldn't be an issue.
• 24:59
  It really wouldn't.
• 25:00
  Well, we are all out of time for today.
• 25:03
  Thank you, Alina, for jumping in this week, and thank you, Charles, for joining in as well.
• 25:07
  Please like and subscribe.
• 25:09
  Share with friends.
• 25:10
  We will talk with you all next week.
• 25:12
  Thank you.